OBJECTIVES: Empirical evidence of discriminative validity is required to justify the use of mechanisms-based classifications of musculoskeletal pain in clinical practice. The purpose of this study was to evaluate the discriminative validity of mechanisms-based classifications of pain by identifying discriminatory clusters of clinical criteria predictive of "nociceptive," "peripheral neuropathic," and "central sensitization" pain in patients with low back (± leg) pain disorders. METHODS: This study was a cross-sectional, between-patients design using the extreme-groups method. Four hundred sixty-four patients with low back (± leg) pain were assessed using a standardized assessment protocol. After each assessment, patients' pain was assigned a mechanisms-based classification. Clinicians then completed a clinical criteria checklist indicating the presence/absence of various clinical criteria. RESULTS: Multivariate analyses using binary logistic regression with Bayesian model averaging identified a discriminative cluster of 7, 3, and 4 symptoms and signs predictive of a dominance of "nociceptive," "peripheral neuropathic," and "central sensitization" pain, respectively. Each cluster was found to have high levels of classification accuracy (sensitivity, specificity, positive/negative predictive values, positive/negative likelihood ratios). DISCUSSION: By identifying a discriminatory cluster of symptoms and signs predictive of "nociceptive," "peripheral neuropathic," and "central" pain, this study provides some preliminary discriminative validity evidence for mechanisms-based classifications of musculoskeletal pain. Classification system validation requires the accumulation of validity evidence before their use in clinical practice can be recommended. Further studies are required to evaluate the construct and criterion validity of mechanisms-based classifications of musculoskeletal pain.
OBJECTIVES: Empirical evidence of discriminative validity is required to justify the use of mechanisms-based classifications of musculoskeletal pain in clinical practice. The purpose of this study was to evaluate the discriminative validity of mechanisms-based classifications of pain by identifying discriminatory clusters of clinical criteria predictive of "nociceptive," "peripheral neuropathic," and "central sensitization" pain in patients with low back (± leg) pain disorders. METHODS: This study was a cross-sectional, between-patients design using the extreme-groups method. Four hundred sixty-four patients with low back (± leg) pain were assessed using a standardized assessment protocol. After each assessment, patients' pain was assigned a mechanisms-based classification. Clinicians then completed a clinical criteria checklist indicating the presence/absence of various clinical criteria. RESULTS: Multivariate analyses using binary logistic regression with Bayesian model averaging identified a discriminative cluster of 7, 3, and 4 symptoms and signs predictive of a dominance of "nociceptive," "peripheral neuropathic," and "central sensitization" pain, respectively. Each cluster was found to have high levels of classification accuracy (sensitivity, specificity, positive/negative predictive values, positive/negative likelihood ratios). DISCUSSION: By identifying a discriminatory cluster of symptoms and signs predictive of "nociceptive," "peripheral neuropathic," and "central" pain, this study provides some preliminary discriminative validity evidence for mechanisms-based classifications of musculoskeletal pain. Classification system validation requires the accumulation of validity evidence before their use in clinical practice can be recommended. Further studies are required to evaluate the construct and criterion validity of mechanisms-based classifications of musculoskeletal pain.
Authors: Tom G Mayer; Randy Neblett; Howard Cohen; Krista J Howard; Yun H Choi; Mark J Williams; Yoheli Perez; Robert J Gatchel Journal: Pain Pract Date: 2011-09-27 Impact factor: 3.183
Authors: Randy Neblett; Howard Cohen; YunHee Choi; Meredith M Hartzell; Mark Williams; Tom G Mayer; Robert J Gatchel Journal: J Pain Date: 2013-03-13 Impact factor: 5.820